(159l) Mixture Solubility Parameters from Experimental Data and Perturbed-Chain Statistical Associating Fluid Theory

Solubility parameters are often used as a screening tool to identify candidate solvents. For single components, solubility parameters are well documented. However, in the industrial setting, solvents are rarely composed of a single component. Surprisingly, there are very few studies in the literature which discuss compositional effects on multi-component solubility parameters. Further, we were not able to locate a single study which provided a detailed study of mixture solubility parameters.

In this work we apply the polar PC-SAFT equation of state to calculate the solubility parameters of liquid mixtures. We validate the theoretical predictions against “experimental” mixture solubility parameters which are constructed using the thermodynamic definition of the solubility parameter, and readily available data including the pure component solubility parameters, enthalpies of mixing, and change in volume of mixing.

It is shown that the solubility parameter of mixtures which exhibit mild solution non-idealities can be adequately described by an ideal solution solubility parameter model. However, for mixtures which have large enthalpies of mixing, the ideal solution assumption fails. For these non-ideal mixtures polar PC-SAFT is able to accurately predict the mixture solubility parameters.